Michael Shuler,
Samuel B. Eckert Professor of Engineering,
Cornell University, President Hesperos, Inc.
Michael L. Shuler is the Eckert Professor of Engineering, Emeritus in the Meing Department of Biomedical Engineering and in the Smith School of Chemical and Biomolecular Engineering at Cornell University, and was director of Cornell’s Nanobiotechnology Center. Shuler has degrees in chemical engineering (BS, Notre Dame, 1969 and Ph.D., Minnesota, 1973) and has been a faculty member at Cornell University since 1974. Shuler’s research includes development of “Body-on-a-Chip” for testing pharmaceuticals for toxicity and efficacy, creation of production systems for useful compounds, such as paclitaxel from plant cell cultures, and construction of whole cell models relating genome to physiology. Shuler is CEO and President of Hesperos, a company founded to implement the “Body-on-a-Chip” system. Shuler and F. Kangi have authored a popular textbook, “Bioprocess Engineering; Basic Concepts” now in its third edition. He has an honorary doctorate from the University of Notre Dame. Shuler has been elected to the National Academy of Engineering and the American Academy of Arts and Science and is a fellow of numerous professional societies.
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Human “Body-on-a-Chip” Systems to Test Drug Efficacy and ToxicityMonday, 10 July 2017 at 11:00 Human microphysiological or “Body-on-a-Chip” systems are powerful tools to assess the potential efficacy and toxicity of drugs in pre-clinical studies. Having a human based, multiorgan system, that emulates key aspects of human physiology can provide important insights to complement animal studies in the decision about which drugs to move into clinical trials. Our human surrogates are constructed using a low cost, robust “pumpless” platform. We use this platform in conjunction with “functional” measurements of electrical and mechanical activity of tissue constructs (in collaboration with J. Hickman, University of Central Florida). Using a system with four or more organs we can predict the exchange of metabolites between organ compartments in response to various drugs and dose levels. We will provide examples of using the system to both predict the response of a target tissue as well as off-target responses in other tissues/organs. We believe such models will allow improved predictors of human clinical response from preclinical studies.
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